5 Frequent Analytics Challenges for Snowflake Customers

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There are a plethora of instruments and platforms to select from in terms of constructing  dashboards with Snowflake information. For constructing interactive analytics apps with Snowflake, there’s GoodData.

GoodData and Snowflake make a superb mixture for operating your analytics app. Your subsequent query is why, proper? The reply is a bit long-winded however learn on to be taught in regards to the 5 distinctive use circumstances GoodData gives to help Snowflake information customers.

1. Eradicate Change-request Overload

The State of affairs

In analytics, one measurement doesn’t match all. Finish customers will all the time be on the lookout for one thing straight suited to their wants (i.e., a distinct view of the information). This results in your workforce will rapidly turn into inundated with customization requests.

GoodData Resolution

That is the place multi-tenant structure, a widely known GoodData staple, turns into a necessity. By offering separate workspaces — devoted areas the place customers can analyze their information and look at their dashboards — for every shopper firm or consumer group, you’ll be able to simply allow end-user customizations of dashboards and stories whereas guaranteeing that every group’s information is separate and safe. On high of this, with plans priced per workspace fairly than per consumer and the flexibleness so as to add limitless customers per workspace, you’ll be able to rapidly and simply scale your product alongside together with your Snowflake information warehouse.

2. Scale Analytics Alongside Snowflake Knowledge Storage With out Sacrificing Efficiency

The State of affairs

Whether or not you intend to roll out analytics internally to workers or externally to prospects, one of many most important targets to your analytics answer will probably be to supply analytics to as a lot of your finish customers as potential. Nevertheless, the flipside to that is that as your end-user uptake will increase, so do the efficiency necessities of your information storage and your analytics. As well as, profitable analytics functions are fairly taxing from an operational perspective. As your utility good points traction, you’ll quickly see information volumes and concurrent consumer numbers develop, together with the prevalence of peak utilization occasions.

GoodData Resolution

On this occasion, elastically scalable analytics is required to enrich your Snowflake information warehouse. GoodData’s elastic scalability effectively scales by information quantity, consumer quantity, and value; in order your Snowflake information storage grows, your analytics and consumer numbers can scale together with it — with out sacrificing efficiency.

3. Leverage Reusable Metrics to Empower Finish Customers

The State of affairs

Whereas multi-tenant structure is one major requirement for offering self-service analytics, one other problem is knowing who your finish customers will probably be. They probably gained’t all be analysts by career, which is why each step in the direction of ease of customization is efficacious. It additional helps to forestall customization requests that might in any other case go to your product, help, or skilled providers groups.

GoodData Resolution

GoodData’s answer is to implement reusable metrics. Reusable metrics is the best approach to obtain ease of customization. By making a semantic mannequin and defining base metrics that your finish customers can later use when creating their particular metrics as easy arithmetic expressions, your finish customers can handle their analytics effectively and confidently.

Data model example
Outline base metrics your finish customers can reuse.
Logical data model with stacks of technical and business metrics
Obtain ease of customization with reusable metrics.

4. Get rid of Knowledge Silos and the Must Transfer Knowledge

The State of affairs

With information being collected from a number of sources and moved between departments and functions, the prevalence of information silos and rancid information is a typical downside for corporations rolling out analytics.

GoodData Resolution

Your Snowflake information warehouse solves a part of the equation by offering one location for storing your whole information from scattered information sources. The opposite half of the equation? GoodData Cloud to straight question your Snowflake information in actual time for all the time up-to-date information analytics — with out the necessity to transfer information whereas additionally eliminating information silos.

5. Keep away from Metrics Inconsistencies

The State of affairs

As described above, with an analytics answer straight querying your Snowflake information in actual time, finish customers all the time have entry to the freshest information. On the similar time, you keep away from the necessity to transfer information. Nevertheless, a profitable analytics utility will probably contain a variety of customers, analysts, builders, and information scientists who gained’t be happy with simply interactive information visualizations and dashboards.

They’ll wish to use the analytics leads to a number of different functions (e.g., BI instruments, ML/AI notebooks, and so forth.) that type a part of their workflow and mix these leveraged metrics with their queries. As a substitute of counting on outdated information exports, they’ll wish to hook up with the semantic layer and get real-time metrics, reminiscent of utilizing their Python code with GoodData Python SDK.

Many corporations strategy this want through the use of a number of instruments and platforms that sit on high of a shared database. Nevertheless, guaranteeing analytics consistency throughout these varied instruments is troublesome as a result of every software can use a distinct information mannequin and question language in addition to snapshots of information from totally different occasions. All of those variations may cause customers to make use of ungoverned calculations of their instruments. Unsurprisingly, this results in information inconsistencies when 4 customers report 4 totally different values of the identical KPI.

GoodData Resolution

Right here is the place headless BI is the answer. Headless BI permits finish customers to attach on to the analytics engine embedded in your functions by way of commonplace APIs and protocols (e.g., JDBC or ODBC) to supply up-to-date, clearly outlined information.

Headless BI schema
Guarantee constant analytics outcomes with headless BI.

Strive GoodData + Snowflake

Need to be taught extra about methods to get essentially the most out of your Snowflake information with GoodData? Learn extra about the advantages of our technical partnership or request a demo as we speak and we’ll offer you an in-depth guided tour.

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